Establishment of a Stochastic Model for Sustainable Economic Flood Management in Yewa Sub-Basin, Southwest Nigeria
Abstract
Of all natural disasters, floods have been considered to have the greatest potential damage. The magnitude of economic damages and number of people affected by flooding have recently increased globally due to climate change. This study was based on the establishment of a stochastic model for reducing economic floods risk in Yewa sub-basin, by fitting maximum annual instantaneous discharge into four probability distributions. Daily discharge of River Yewa gauged at Ijaka-Oke was used to establish a rating curve for the sub-basin, while return periods of instantaneous peak floods were computed using the Hazen plotting position. Flood magnitudes were found to increase with return periods based on Hazen plotting position. In order to ascertain the most suitable probability distribution for predicting design floods, the performance evaluation of the models using root mean square error was employed. In addition, the four probability models were subjected to goodness of fit test besed on Anderson-Darling (A2) and Kolmogorov-Smirnov (KS). As a result of the diagnostics test the Weibul probability distribution was confirmed to fit well with the empirical data of the study area. The stochastic model generated from the Weibul probability distribution, could be used to enhance sustainable development by reducing economic flood damages in the sub-basin.
Keywords
References
Ismail, Ahmad Zuhdi, Zulkifli Yusop, and Zainab Yusof. "COMPARISON OF FLOOD DISTRIBUTION MODELS FOR JOHOR RIVER BASIN." Jurnal Teknologi 74, no. 11 (2015): 123–128.
Agbede A.O and Abiona. Plotting Position Probability Fittings to Lagos Metropolitan Precipitation: Hydrological Tools for Hydraulic Structures Design in Flood Control. International Journal of Pure and Applied Sciences and Technology. 10 (2012): 37-43.
UNESCO. Concepts in Probability, Statistics and Stochastic Modelling. Water Resources Systems Planning and Management Report. 2005.
Vivekanandan, N. Comparison of Probability Distributions for Estimation of Peak Flood Discharge. Open Access Library Journal, 1 (2014): e498.
Kochanek, K. B. Renard, P. Arnaud, Y. Aubert, M. Lang, T. Cipriani, and Sauquet, E. A data based comparison of flood frequency analysis methods used in France. Nat. Hazards Earth Syst. Sci., 14 (2014): 295–308.
Vivekanandan, N. Assessing Adequacy of a Probability Distribution for Estimation of Design Flood. Bonfring International Journal of Industrial Engineering and Management Science. 2(2012): 22-27.
Oyebande, L. and Adeaga, O. Flow simulation in an ungauged basin using a digital elevation model. Predictions in Ungauged Basins: PUB Kick-off (Proceedings of the PUB Kick-off meeting held in Brasilia, 20–22 November 2002). IAHS Publ. 309, 2007.
Tilahun K. The Characterization of Rainfall in the arid and semi arid regions of Ethiopia, Water SA, 32(2006), 429-439.
Coles, S. An Introduction to Statistical Modeling of Extreme Values. New York: Springer Verlag. 2001.
Millington, N., Samiran Das and S. P. Simonovic. The Comparison of GEV, Log-Pearson Type 3 and Gumbel Distributions in the Upper Thames River Watershed under Global Climate Models. Water Resources Research Report. 2011.
Fasinmirin J.T. and Olufayo A.A. Comparison Of Flood Prediction Models For River Lokoja, Nigeria. Department of Agricultural Engineering, Federal University of Technology, Akure, Nigeria. 2006.
Adeboye, O. B. and Alatise, M. O. Performance of Probability Distributions and Positions in Estimating the Flood of River Osun at Apoje Sub-basin Nigeria. Agricultural Engineering International: the CIGR Ejournal. 9(2007).
DOI: 10.28991/cej-2016-00000065
Refbacks
- There are currently no refbacks.
Copyright (c) 2017 O.A Agbede, Oluwatobi Aiyelokun
This work is licensed under a Creative Commons Attribution 4.0 International License.
